Analog signal processing in optical systems is a field that harnesses the unique properties of light to manipulate and analyze continuous signals. Unlike digital processing, where signals are discretized, optical analog processing operates directly on the continuous variations in light's intensity, phase, frequency, or polarization. This approach is fundamental in applications such as telecommunications, imaging, and sensing, where the inherent speed, bandwidth, and parallelism of optical systems provide significant advantages. Despite its advantages, challenges like precision alignment and integration with electronic systems remain areas of ongoing research and innovation. This field continues to evolve, offering promising solutions for high-speed, high-bandwidth signal processing. In this dissertation we will look at 3 different optical systems that use analog signal processing to enhance the performance of the systems.In Chapter 1, we study Swept Source Optical Coherence Tomography and LiDAR. We demonstrate a novel approach, which we call Universal Photonics Tomography, based on the use of phase modulation combined with multirate signal processing to collect positional information of objects beyond the Nyquist limits. In Chapter 2, we study a similar approach for Spectral Domain Optical Coherence Tomography. We theoretically formulate the use of phase modulators and delay lines to act as filters on the tomography system and scan multiple channels. Various channels are then combined in a digital computer using filter bank theory to improve the sampling rate. In Chapter 3, we study Physical Reservoir Computing (PRC). We theoretically analyze the performance of photonic waveguide mesh (WGM) with electro-optic phase shifters for Monolithic-Hybrid-Photonic-Electronic Reservoir Computing (MHPE RC). Next, we present the Lyapunov filtered-minimal Redundancy Maximal Relevance (Lf-mRMR) algorithm which optimizes the electronic parameters of parallel WGMs by analyzing the Lyapunov exponent and the mutual information between the output of the corresponding WGMs and the required task. We also present the Selective Parallel Architecture for Reservoir Computing (SPARC), Finally, we experimentally employ on-chip silicon photonic device to validate the advantageous performance of Lf-mRMR assisted RC.